Triple
T2256503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Swanson |
E49738
|
entity |
| Predicate | coFounded |
P104
|
FINISHED |
| Object | Genentech |
E7901
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Genentech | Statement: [Robert Swanson, coFounded, Genentech]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Genentech Context triple: [Robert Swanson, coFounded, Genentech]
-
A.
Genentech
chosen
Genentech is a pioneering American biotechnology company known for developing groundbreaking therapies and being one of the first firms to apply genetic engineering to medicine.
-
B.
Janssen Biotech
Janssen Biotech is a biopharmaceutical company known for developing and manufacturing innovative biologic therapies, including the blockbuster monoclonal antibody Remicade.
-
C.
Genmab
Genmab is a Danish biotechnology company specializing in the development of antibody-based cancer therapies.
-
D.
Novartis
Novartis is a global Swiss-based pharmaceutical company known for developing innovative medicines across a wide range of therapeutic areas.
-
E.
Regeneron Pharmaceuticals
Regeneron Pharmaceuticals is a leading American biotechnology company known for developing innovative antibody-based therapies for serious diseases, including eye disorders, cancer, and inflammatory conditions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a88aaa9250819095e127d0d77e8a32 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc1570dc88190bb2b17ed4c25dbb5 |
completed | March 7, 2026, 6:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae7f067f208190a399e2b1a83badd1 |
completed | March 9, 2026, 8:04 a.m. |
Created at: March 4, 2026, 7:47 p.m.